Straits Institute for Applied AI
Catalogue/Tier 3 · Job Skills/Research & Media
AI+ for Textual & Discourse Analysis cover
T3-87 · Tier 3 · Job Skills

AI+ for Textual & Discourse Analysis

Analyse Language, Discourse and Meaning with AI

You need to code 300 transcripts. Manually, that's three weeks. With a principled framework, it's three days — and every decision is documented.

You're coding transcripts manually at midnight, knowing you can't finish the corpus before the deadline. Or you've used ChatGPT for summaries but couldn't defend the method in your supervision meeting. AI can scale your analysis — but only if you know where it belongs and where it doesn't. The DECODE Protocol maps six stages of textual and discourse analysis, with over 30 prompt templates spanning content coding, CDA feature extraction, corpus linguistics, narrative mapping, and write-up across four genres. Built by an AI engineering firm for researchers who know how to read texts — and need AI to extend their reach without compromising what makes their analysis intellectually serious.

Tier
Tier 3 · Job Skills
Category
Research & Media
Format
Guide
Updated
Q2 2026
Inside
  • 30+ ready-made prompt templates: content coding schemes, CDA feature extraction, KWIC concordance interpretation, narrative structure mapping, and four write-up genres
  • The DECODE Protocol — the six-stage AI-assisted discourse analysis framework covering every major tradition from corpus linguistics to conversation analysis
  • A validation workflow for AI-assisted coding: training sample, validation pass, inter-rater agreement, and the methods-section attribution paragraph that satisfies peer review
  • Comparative corpus analysis: how to map how two institutional corpora represent the same issue — at a scale manual reading can't reach
  • A 90-day action plan with month-by-month checks, a personal prompt library, and an AI practice statement for supervision meetings and ethics submissions
Who this is for

Qualitative researchers, communication scholars, linguists, humanities academics, and postgraduate students who analyse texts — interviews, documents, media, social media, policy papers, literary works — and want to use AI to work faster and more rigorously without compromising methodological integrity

Also for:Applied researchers and analysts in policy, NGOs, UX, and market research who regularly work with large volumes of text and need a structured, ethical approach to AI-assisted analysis; journalism and media studies researchers examining discourse in news, social media, or political communication

You’ll be able to
  • Construct, prepare and ethically manage a text corpus for AI-assisted analysis
  • Apply the DECODE Protocol to structure an end-to-end textual or discourse analysis project with AI at each stage
  • Conduct AI-assisted content analysis, including scheme development, coding, and pattern detection, while preserving analytical integrity
  • Apply core discourse analysis methods — critical discourse analysis, corpus linguistics, narrative analysis, frame analysis — with AI as a research assistant
  • Write up and report discourse analysis findings, with clear attribution of AI assistance in methods sections
What’s inside
Diagnostic
How ready are you to use AI in your textual and discourse analysis?
Chapter 1
AI in Textual and Discourse Analysis Right Now
Chapter 2
Building and Preparing Your Text Corpus
Chapter 3
AI-Assisted Content Analysis and Coding
Chapter 4
Critical Discourse Analysis with AI
Chapter 5
Corpus Linguistics Techniques
Chapter 6
Narrative and Frame Analysis
Chapter 7
Conversation and Interactional Analysis
Chapter 8
Multimodal and Digital Discourse
Chapter 9
Writing Up Textual and Discourse Findings
Chapter 10
Your Textual Analysis Action Plan
Back matter
Skill Summary · Recommended Next Reads · Glossary · Tool Reference

Built by an AI engineering firm for researchers who know how to read texts — and need AI to extend their reach without compromising what makes their analysis intellectually serious.

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How this was made

Every AI+ title is written by AI engineers who build production AI systems, then verified by practising professionals in the field it serves. Titles are reviewed quarterly and updated whenever the technology or regulation shifts. Localised editions are reviewed by in-region experts before release.

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